>> Hello everybody, this is
Lara Rubbelke and I'm here with Azure Friday,
our a special edition,
Azure Friday on the go here at the Build conference.
Today, I'm here with Ahmed Ashour and he is
a dev on our LUIS framework.
So, we're going to be talking
about some of our Cognitive Services for
language and the things that our developers are
doing to build intelligence into their application.
So talk to me about the different kinds of
Cognitive Services that we
have delivered out for our customers.
>> Cognitive Services are
a set of services that Microsoft
offers to people to democratized machine learning.
So, we specialized in
language and in the specialty of language,
we have some services one
of them is called Text analytics.
>> Yeah.
>> One of them is called machine
translation whereas the Bing Spell Check,
Bing Custom Search, and Language
Understanding Intelligent Service or LUIS.
>> Okay.
>> So, for the Text analytics, basically,
we have some prebuilt models that allow
you to check for
the sentimental analysis of the text that you send,
extract key phrases, and things like that.
In the Bing Spell Check, well,
as the name suggest, it's spell checks your text.
For Bing Custom Search,
you get to build your own Bing
like search index on whatever websites you want.
>> Okay.
>> For QnA Maker,
you build your own question-answering system.
>> Right. That's basically you can feed it like a FAQ.
>> Yeah, exactly.
>> But it's straight into the.
>> Exactly. And generates the questions and answers.
>> Yeah, and it just builds up the whole model for you.
>> Exactly.
>> That's pretty cool stuff.
So, talk to me a little bit more.
As a developer, all I need to do is wire up,
set up my Cognitive Service for-
>> It's pretty simple. The way we built our services is,
for people who do not have
any machine learning background,
it would be like a walk in
the park to just create a new application.
>> Yeah.
>> Provided with some examples, publish it,
and just put it
or to make in their apps and they're good to go.
>> Right. So you go to the Azure portal for example,
you say give me a new Cognitive Service,
you choose which service you want, and then.
>> Some services have their own prebuilt models.
>> Okay.
>> Some services allow you to customize
your own models to fit your own needs,
and you just plug it in your app and you're good to go.
>> Great. So, you just get a key and then you
basically wires up that connectivity
between your app and the Cognitive Service,
and then all you need to do is supply with
some data and you are getting responses.
Yeah, it makes it super easy to build intelligence.
Fantastic. Now, you talked about
LUIS and you're actually building LUIS.
>> Yeah.
>> What does LUIS that stand for?
I love LUIS so.
>> Well, LUIS stands
for the Language Understanding Intelligent Service.
It is a part of Microsoft Cognitive Services
and it specializes in
allowing customers to create
their own custom intent classified as entity extractors.
So basically, it create
their own language understanding applications
to use them depending on their own needs.
So, LUIS will allow you to, basically,
let's get a step back
and describe what are intents and entities.
So intents are the users intention when he
provides you a set of
words or a text. So when you search.
>> So, you get some snippet of a phrase or
something is spoken or written,
and then it's entered into it and LUIS extrapolates.
>> Yeah, exactly, and returns
you the intents and entities
that are recognized in
this text based on what the model that you've built.
>>Okay.
>> So for example, when you
go to bing.com and you search for,
"What's the birthday of Barack Obama?"
You get the answer right away that tells
you the birthday of Barack Obama and so and so.
How does this work? Well, Bing
has its own intent classifiers, entity extractors.
>> Right.
>> For intent classifiers,
it basically knows that,
what is Barack Obama has
the intention of getting information.
>> Right.
>> So, it knows that it has to trigger one of
the many informational answers that it has,
and it extracts that you're looking for the birthday,
which is personal attribute,
and Barack Obama which is a person.
So, Barack Obama and birthday are
both entities and the intent is informational,
so we're basically asking about
the birthday of Barack Obama.
>> Right.
>> It looks up its own knowledge base
and returns the answer as
an answer on Bing
saying that the birthday of Barack Obama is so and so.
So basically, those are, that's
a brief discussion for intents and entities.
What LUIS provides is a simple way to allow users,
who have no machine learning background,
to just create an app and build
an own custom intents and custom entities on web,
some of our prebuilt intents and entities,
and just use it
without having to have any idea about machine learning.
>> So, what are some examples of the intents
and entities that you have
provided that get people started?
>> Well, we have a set of
prebuilt entities or a prebuilt domains.
So basically, our prebuilt entities include numbers,
ordeals, adverses, emails, things that can detect-
>> It's common things that you don't-
>> Exactly.
>> Yeah.
>> But even more,
we allow users to create their own
custom intents and entities.
So for example, if you're building a travel agent bot,
you might need something to understand the lingo and
the intents and entities that
the travel agent might have to deal with.
>> Right.
>> So, you get to create a LUIS app
that basically distinguishes
between book flight intent,
a cancel a flight intent,
or check my flight info.
So, those three intents you have,
and then you can train it to
extract entities like the source location,
the destination location, the day time of the fight,
the flight number, airport names,
and things like that. So you get to build your own.
>> It constructs the response out
of all of those entity mapping.
>> You just train it, provide it with some examples,
like some amounts of examples,
like between tens of examples or something like that,
and you train it, and you publish it,
and you get presented with a URL,
a REST API that you can just call or embed in your app.
The cool thing about LUIS is,
it provides you with a feedback circle.
>> Right.
>> So, whatever the users send to your LUIS API,
you get feedback to your application and you
can retrain it using those example.
>> So, it just continues to learn and get
better over time the more you use it.
So you build these bots on top of your LUIS model,
the bots starts going viral,
that LUIS model just continues to get.
>> Exactly. Getting better and better.
>> Smarter and smarter.
Okay. Where can go learn more?
>> You can go to microsoft.com/cognitive.
>> Okay.
>> That's the entrance for all of
Microsoft Cognitive Services. So find us there.
>> Great. Well, thank you very much for the time today.
>> Thank you.
>> Once again, this is
Azure Friday and we've been learning about
Cognitive Services with our text in LUIS.